1. Field of the Invention
The invention relates to a method of generating a halftoned image from an image compressed by a domain transformation yielding coefficients for resulting domain components and by a coding operation by which these coefficients are coded, wherein the method includes a decoding operation by which decoded coefficients (yp) are obtained and a thresholding operation by which a bitmap is obtained.
2. Discussion of the Related Art
Image compression technology offers valuable solutions to the problems of high storage or transmission costs. It is widely used in the areas of scanners, printers, facsimile, desktop publishing, medical imaging, graphic arts and many other continuous-tone or colour image applications. As a result of compression, the stream of data becomes shorter and thus, it is better transferred, stored and managed.
Many compression algorithms exist, for example, TIFF CCITT, JBIG and JPEG. JPEG (Joint Photographic Experts Group) has developed a general-purpose compression standard that meets the needs of many continuous-tone image applications. A detailed description is available in Communications of the ACM, 34, p 31 (1991), by G. K. Wallace. JPEG is based on the compression of an image converted firstly in the frequency domain. Source image samples are first grouped in 8×8 blocks. Then the input raw pixel representation is modified, using for example a frequency domain transform like the Discrete Cosine Transform (DCT). So-called DCT coefficients are obtained, which coefficients can be regarded as the relative amounts of the 2D spatial frequencies contained in the 64-point input signal. The coefficient with zero frequency in both dimensions is called the ‘DC coefficient’ while the remaining 63 coefficients are called the ‘AC coefficients’. The DCT coefficients are then quantized, i.e. each DCT coefficient is divided by its corresponding quantizer step size, followed by rounding to the nearest integer. The goal of this operation is to discard information which is not visually significant. This is the reason why quantization is fundamentally ‘lossy’.
It is convenient to order the DCT coefficients in a zigzag sequence of an 8×8 array. In this zigzag sequence, the DC coefficient is coefficient with an index 0 and the higher frequency coefficients have a higher index. This ordering facilitates the next step of compression, being entropy coding, by placing the low-frequency coefficients before the high-frequency coefficients. The step of entropy coding achieves efficient compression by encoding the DCT coefficients more compactly based on their statistical characteristics. Examples of entropy coding methods are the Huffman coding and arithmetic coding.
A benefit from the compressed-domain image processing is the ability to decrease the requirements in terms of processing power. When wide format documents have to be printed, an operation that can be quite time-consuming is the halftoning step due to the large amount of data. In order to perform a print of a compressed image, for example, an image compressed in the JPEG format, the encoded data first have to be decoded. This can be done using a Huffman decoder, by which decoded DCT coefficients are obtained. This operation is followed by a de-quantization step. In order to retrieve the input pixel values, an inverse Discrete Cosine Transform is carried out. Halftoning, being the process of rendering colour or grey-scaled images into bitmaps, i.e. images which pixel values can only have two possible levels (print a dot or do not print a dot), can be performed on these retrieved input pixel values. Examples of well-known halftoning methods are the error diffusion method and the masking method. In the masking method, the halftoning operation is a simple thresholding of an image with a mask that can have different threshold values which are organized in a matrix array. For the sake of efficiency, however, the image processing operations have to be adapted to be performed on the compressed stream of data. This is particularly relevant for wide format documents, because the gain in processing time may be significant.
An image processing operation performed on the compressed stream of data is disclosed for example in PCT Application Publication No. WO 94/22108. According to the method of generating thumbnail or reduced size images disclosed in that document, the images are generated based on the DC values of the DCT coefficients. A Huffman decoder is used to decode the compressed image data, by which quantized DCT coefficients are generated. The steps of de-quantization and of inverse DCT on the AC coefficients are skipped. Only DC coefficients are used to generate an image having a reduced size. In other words, the thumbnail image is built out of the DC values of each 8×8 block. Thus, the process time needed to render the image is reduced, and the user is enabled to quickly browse various images. This method, however, when applied to generating a halftoned image from a compressed image, has the disadvantage that the quality of the rendered details in the printed image is much too low and does not meet the requirements of the user.